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Resume

Current Position

Software Engineer at NModes

Since: September 2022
At: Toronto - Ontario, Canada (remotely)

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Recent Experience

Full Stack Developer / Post-Doc Fellow at University of Manitoba

Period: February 2023 to February 2024
At: Winnipeg - Manitoba, Canada (remotely)

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Research and Teaching Assistant at McMaster University

Period: September 2018 to August 2022
At: Hamilton - Ontario, Canada (on-site)

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Software Engineer at IIHR - Hydrosciences and Engineering

During: May 2017 to August 2018
At: Iowa City - Iowa, USA (on-site)

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Education

Ph.D. | Hydroinformatics - A.I. for flood forecasting

Thesis: Using Machine Learning Techniques to Improve Operational Flash Flood Forecasting
On: December 2022
From: McMaster University - Faculty of Engineering
At: Hamilton - ON, Canada

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M.Sc. | Hydroinformatics - Hydrologic data visualization

Thesis: A web-based GUI for visualization, comparison and evaluation of distributed hydrologic model outputs
On: May 2017
From: The University of Iowa - College of Engineering
At: Iowa City - IA, USA

Bachelor | Environmental Engineering

On:March 2015
From: Paulista State University - UNESP
At: Presidente Prudente - SP, Brazil

Bachelor | Computer Sciences

On: December 2009
From: Campinas State University - UNICAMP
At: Campinas - SP, Brazil

Languages

  • English (fluent)
  • Spanish (fluent)
  • Portuguese (mothertongue)
  • French (intermediare)

Publications

Zanchetta, A.D.L.; Coulibaly, P.; Fortin, V. (2022). Forecasting High-Flow Discharges in a Flashy Catchment Using Multiple Precipitation Estimates as Predictors in Machine Learning Models. Hydrology, 9(12).

Zanchetta, A.D.L.; Coulibaly, P. (2022). Probabilistic Forecasts of Flood Inundation Maps Using Surrogate Models. Geosciences, 12(11).

Velasquez, N.; Mantilla, R.; Krajewski, W.; Quintero, F.; Zanchetta, A.D.L. (2022). Identification and Regionalization of Streamflow Routing Parameters Using Machine Learning for the HLM Hydrological Model in Iowa. Journal of Advances in Modeling Earth Systems, 14(7).

Zanchetta, A.D.L.; Coulibaly, P. (2022). Hybrid Surrogate Model for Timely Prediction of Flash Flood Inundation Maps Caused by Rapid River Overflow. Forecasting, 4(1).

Zanchetta, A.D.L.; Coulibaly, P. (2020). Recent Advances in Real-Time Pluvial Flash Flood Forecasting. Water, 12(2): 570.